The present invention relates generally to the field of product manufacturing optimization, and more particularly to methods for optimizing a layout of selected parts to be cut from pieces of raw material, such as employed in the lumber processing industry.
Product manufacturing optimization techniques have been developed during the past years to improve productivity associated with industrial processes such as manual and automated part cutting or sawing. Generally, such optimization techniques allow the determination of the arrangement of parts that provides the highest yield in terms of raw material usage and/or economic value from a given piece of raw material characterized by the presence of defects that have previously been qualified and located by spatial coordinates within a reference system, which can be either bi-dimensional or tri-dimensional to consider the two opposed main faces of the piece of raw material or the two pairs of opposed surfaces, depending upon the specific application considered. Typically, information about a set of parts to be cut from a piece of raw material is defined by a processing bill or order, which information includes requested quantities for each type of parts, quality grade associated to each requested product, geometrical characteristics such as length and width, unit cost, identification code, etc. Product cutting optimization is usually performed by a computer software which seeks to comply with a requested quantity of parts as set by the cutting bill, while optimizing the spatial arrangement of requested parts in order to maximize raw material usage and/or economic value obtained from the piece of raw material employed. Typically, an optimization software may provide production information details such as raw material yield, economic value yield or pricing, cutting layout, parts distribution, required number of cut operations, etc. Known optimization computer software is typically designed to be integrated into production equipment such as automated sawmill machinery or to be used as stand-alone systems for performing simulation from production data. In lumber processing, especially regarding hardwood cutting into wooden products such furniture components, panels and flooring pieces, crosscut-first rough mill operation has been considered as the main type of cutting process. However, shortage in large pieces of timber, raw material pricing increase and trends in the lumber industry toward diversified products as well as higher production rates have oriented some sawing mills toward rip-first cutting processes, so that both crosscut-first and rip-first processes are now basic sawing processes employed in existing sawing mills. Crosscut-first and rip-first processes having their respective advantages and drawbacks, and depending upon the production context within which they are applied, product cutting performance observed for each of these main processing approaches may vary, rendering the task of cutting process selection a quite difficult one, as extensively discussed in the literature, such by Wiedenbeck, J. K. in xe2x80x9cDeciding between Crosscut and Rip-first processingxe2x80x9d, Wood and Wood Products, August, 2001. Generally, rip-first process provides efficient elimination of defect areas adjacent the edges of the raw material piece, being more easily eliminated within a single section, while cross-cut process provides efficient elimination of defect areas that are located over a short length portion of the piece by removing the whole defective portion. Most of the usual sawing processes favours the segmentation of each piece into a plurality of sections, such as rip-cut or crosscut sections, optimizing raw material surface according to a first reference axis, as discussed by Thomas, R. E. in xe2x80x9cROMI-RIP version 2.0: a new analysis tool for rip-first rough mill operationsxe2x80x9d, Forest Products Journal, vol. 49, no.5, p. 35-40, 1999. Such sections are then further processed to eliminate defect areas while complying with dimensional requirements, such as discussed by Thomas, R. E. et al in xe2x80x9cDecision-support software for optimizing rip-first and chop-first systemsxe2x80x9d Scan Pro, 8th international conference on scanning technology and process optimization for the wood products industry. Flooring wood processing, which is a particular type of rip-first process wherein length dimension is undefined in cutting bills, and panel processing, which is a particular type of cross-first process wherein width dimension is undefined, both offer advantages relevant to one-dimensional freedom axis for arranging parts. such one-axis optimization technique is disclosed in U.S. Pat. No. 4,221,974 entitled xe2x80x9cLumber inspection and optimization systemxe2x80x9d issued Sep. 9, 1990 to Muller et al. Another one-axis optimization method is disclosed in U.S. Pat. No. 4,163,321 entitled xe2x80x9cMethod for sequencing the cutting of elongated stockxe2x80x9d issued to Cunningham on Aug. 7, 1979. There is disclosed a method for cutting optimization of elongated stock such as boards of lumber having random unusable lengths containing defects, which method involves products order requirements, waste factors determination, probability assessment of having a given length of usable stock in each grade being processed, and from the information above, determination of the arrangement of parts to be cut at one time which results in the lowest waste for the entire cutting. Another known one-axis optimization method is disclosed in U.S. Pat. No. 4,017,976 entitled xe2x80x9cApparatus and method for maximum utilization of elongated stockxe2x80x9d issued to Barr and al on Apr. 19, 1977, which employs a yield optimization approach for crosscutting of usable lengths of stock such as boards of lumber having random unusable lengths containing defects, wherein lengths of stock required are determined, information describing the required lengths is stored, a value factor for each required length is calculated and stored as well as statistical data describing usable lengths in various grades of stock, information on various grades proportions being processed is stored, priority factors to increase the probability of cutting desired lengths are determined and stored, and finally, based on the information above, the positions of the backgauge indicators are calculated, which represent optimum possible combinations of lengths for each usable length which can be cut into the desired lengths, which position indicators are printed in full scale on a continuous sheet of paper.
In order to improve the performance of optimization over known one-axis techniques, two-axis optimization methods and software have been developed, such as rip-first software discussed by Thomas, R. E. in xe2x80x9cROMI-RIP version 2.0: a new analysis tool for rip-first rough mill operationsxe2x80x9d, Forest Products Journal, vol. 49, no.5, p. 35-40, 1999, as well as crosscut-first software also discussed by Thomas in xe2x80x9cROMI-CROSS: An analysis tool for crosscut-first rough mill operationsxe2x80x9d, Forest Products Journal, Vol. 48, no. 3, pp. 68-72. Such optimization systems allow the generation of an optimal cutting solution which consider two reference optimization axis simultaneously, which solution includes data on selected arrangements of parts, cutting position as well as output yield. ROMI-RIP and ROMI-CROSS are two-axis optimization software products performing successive optimization steps considering quality/grades of products as defined in the cutting bill, from the highest grade to the lowest grade. A similar two-axis optimization technique is disclosed in U.S. Pat. No. 3,329,181 entitled xe2x80x9cApparatus and method for cutting assorted lengths from material having irregular and random defectsxe2x80x9d issued Jul. 4, 1967 to Buss and al. Another two-axis optimization technique is disclosed in U.S. Pat. No. 4,805,679 issued to Czinner on Feb. 21, 1989, which makes use of an expert system for performing the optimization task. Another two-axis apparatus for optimizing the yield of usable piece from boards and the like is disclosed in U.S. Pat. No. 3,942,021 issued to Barr and al on Mar. 2, 1976, which adopts a yield optimization approach wherein a primary bit matrix corresponding to a pattern of scanned unusable defect containing areas of a processed board of lumber, is formed and stored in computer. Predetermined combinable unusable defect containing areas as well as predetermined combinable unusable non-defect containing areas are identified from the primary bit matrix, and the identified combinable unusable defect and non-defect containing areas are merged to produce a list defining a pattern characterizing usable areas. Predetermined billing requirements are established and stored, various cutting patterns for the workpiece are successively determined on the basis of usable area information and billing requirements, and the cutting pattern producing the optimum yield for a workpiece is selected.
Although considered as a promising alternative to conventional one-axis optimization systems in use by rough-mill operations, most of existing two-axis optimization systems are conceived on the basis of optimization methods that do not provide sufficient flexibility to ensure maximum optimization performance in specific applications, and therefore, they have not yet achieved general acceptance within the lumber industry.
It is therefore a main object of the present invention to provide a method of optimizing a layout of selected parts to be cut which allows flexibility of use while ensuring reliable optimization results.
According to the above object, from a broad aspect, there is provided a method of optimizing a layout of selected parts to be cut from a piece of raw material with respect to first and second orthogonal reference axis, using data representing geometric and defect-related characteristics of said piece and data representing geometric and grade characteristics of a set of parts to be cut. The method comprises the steps of: i) defining a subset of the set of parts characterized by a predetermined grade value and associated with a predetermined group of first dimension values defined with respect to the first axis; ii) generating data defining an arrangement of subdivided piece surface sections to be obtained through a primary cut operation with respect to the second reference axis and according to one or more of the first dimension values; iii) generating data defining one or more subsections included in each piece surface section according to the geometric and defect-related characteristics of the piece; iv) generating data defining for each subsection a plurality of arrangements of parts to be included therein and selected from the subset of parts, to be obtained through a secondary cutting operation with respect to the first reference axis; v). estimating yield values associated with the arrangements of parts; vi) comparing the yield values to select one of the arrangements of parts having a highest yield value; vii) estimating a basic yield value the arrangement of subdivided piece surface sections; viii) repeating steps ii) to vii) for one or more new arrangements of subdivided piece surface sections to estimate corresponding basic yield values; and ix) comparing all basic yield values one with another to select the arrangement of subdivided piece surface sections associated with the arrangements of parts providing a maximal basic yield value to be included in the optimized layout of selected parts to be cut.
According to the same main object, from a further broad aspect of the invention, there is provided a software product data recording medium in which program code is stored, which program code will cause a computer to perform a method of optimizing a layout of selected parts to be cut from a piece of raw material with respect to first and second orthogonal reference axis, using data representing geometric and defect-related characteristics of said piece and data representing geometric and grade characteristics of a set of parts to be cut, wherein the method comprises the steps of: i) defining a subset of the set of parts characterized by a predetermined grade value and associated with a predetermined group of first dimension values defined with respect to the first axis; ii) generating data defining an arrangement of subdivided piece surface sections to be obtained through a primary cut operation with respect to the second reference axis and according to one or more of the first dimension values; iii) generating data defining one or more subsections included in each piece surface section according to the geometric and defect-related characteristics of the piece; iv) generating data defining for each subsection a plurality of arrangements of parts to be included therein and selected from the subset of parts, to be obtained through a secondary cutting operation with respect to the first reference axis; v) estimating yield values associated with the arrangements of parts; vi) comparing the yield values to select one of the arrangements of parts having a highest yield value;,:vii) estimating a basic yield value the arrangement of subdivided piece surface sections; viii) repeating steps ii) to vii) for one or more new arrangements of subdivided piece surface sections to estimate corresponding basic yield values; and ix) comparing all basic yield values one with another to select the arrangement of subdivided piece surface sections associated with the arrangements of parts providing a maximal basic yield value to be included in the optimized layout of selected parts to be cut.